US Space Command Applies AI Tools to Operational Planning at APEX Summit
The U.S. Space Command used artificial intelligence to streamline operational planning at the Augmented Planning and Execution (APEX) Summit in Colorado, Nov. 18-21. More than 70 leaders from across the command and its components contributed input to advance the 2026 Coordinated Campaign Order.
Gen. Stephen Whiting called AI "an era-defining technology" with growing relevance to national security and stated the command "must lead the way in ensuring a safe and secure space domain for our nation, our Allies and Partners, and the rest of the world."
Inside the APEX Summit
USSPACECOM split participants into four teams and gave each group access to three different AI tools. Teams curated inputs-procedural documents, references, and manuals-based on campaign objectives and command guidance.
They tested multiple prompting approaches: structured campaign-order prompts, self-directed exploration, and engineer-guided collaboration. Staff then validated AI-generated content before including it in the 2026 Coordinated Campaign Order.
The Strategy Behind It
The summit supports USSPACECOM's AI/Machine Learning and Data Analytics Strategy published in March. The goals were simple and practical: refine the command's approach to human-machine teaming and establish a governance model for responsible AI use in operational planning.
Put differently: experiment with multiple tools and methods, keep humans in the loop, and set clear rules before scaling.
Why Executives Should Care
- Outcome-focused AI: Start with a concrete deliverable (e.g., a campaign order) and work backward to tools and prompts.
- Multi-tool evaluation: Running parallel tools surfaces differences in quality, speed, and reliability you won't see in a single-vendor trial.
- Data curation is strategy: Internal playbooks, SOPs, and references are leverage. Better inputs equal better outputs.
- Human oversight: Validation steps are non-negotiable for accuracy, accountability, and risk management.
- Governance first: Define responsible-use boundaries and decision rights early to avoid rework and audit gaps later.
How to Apply This Model in Your Organization
- Clarify mission outcomes and success metrics for AI-assisted planning.
- Form cross-functional teams (ops, legal/compliance, data, engineering).
- Build a clean corpus of internal procedures, references, and manuals.
- Pilot 2-3 AI systems on the same tasks; compare output quality and cycle time.
- Test multiple prompting modes (structured templates, open exploration, engineer-guided).
- Set a review and approval workflow with documented checkpoints.
- Capture lessons learned, update prompts and playbooks, and version-control everything.
- Track measurable gains (throughput, accuracy, time-to-decision) before scaling.
Context and Resources
For background on the command and its priorities, see the official U.S. Space Command site: USSPACECOM. For governance principles, review the Department of Defense guidance on responsible AI: DoD Responsible AI.
If you're building executive readiness for AI governance, human-machine teaming, and prompt design, explore curated programs such as the AI Learning Path for CIOs and the AI Learning Path for Regulatory Affairs Specialists.
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